Rotational motion estimaiton of high-resoluiton ISAR imaigng for manuvering targets

In this paper, a novel algorithm of rotational parameter estimation is proposed for high-resolution inverse synthetic aperture (ISAR) imaging of maneuvering targets. For a non-uniform rotation target, the signal model is formulated. Then, an entropy minimization approach is used to estimate the rotational parameters, which is solved by using a coordinate descent algorithm based on quasi-Newton method. The estimated parameters are used to rescale the reconstructed ISAR image to extract the target geometry. Finally, experimental analysis is performed to confirm the effectiveness of the proposed algorithm.